Sr. Data Scientist, Monetization

Pinterest Pinterest · Consumer · San Francisco, CA · Engineering, Product and Design (L2)

This role is for a Sr. Data Scientist on the Monetization Engineering team at Pinterest. The primary focus is on analyzing and improving the ads ecosystem through data-driven strategies, modeling, and experimentation. While AI is mentioned as a partner, the core responsibilities revolve around traditional data science tasks like strategic analysis, opportunity sizing, segmentation modeling, experimentation, and metric tracking within the ads domain. The role emphasizes end-to-end ownership of data products and collaboration with cross-functional teams.

What you'd actually do

  1. Deep strategic analysis to answer core questions such as: How do we assess the trade-off between metrics change? How should we evaluate overall impact from changes in one component of the ads ecosystem?
  2. Opportunity sizing and analysis. Should Pinterest adjust programmatic ad load based on ? Write clear, actionable analyses that help teams identify areas of improvement and investment.
  3. Modeling: Build segmentation models to assess supply to inform pricing strategy.
  4. Improve decision velocity and quality using data scientist tool kit: experimentation, causal inference techniques, etc. Design measurement strategy, advise on experimentation best practices, identifying flaws in experiment practices and results; building tools for experiment analysis etc.
  5. Creating and tracking success metrics. Identify the right measures of success for engineering teams and help them track those metrics. Break down high-level metrics into actionable segments. This work may span from collecting entirely new datasets to building dashboards to track components of a metric (e.g., monitoring conversion data for missing values, implausible values, duplicated data, etc. by advertiser over time).
  6. Leadership: Lead and mentor the scope of work for data scientists in the same area, demonstrating high-quality output of both yourself and others for whom you are responsible. Provide continuous and candid feedback, recognizing individual strengths and contributions and flagging opportunities to improve performance.

Skills

Required

  • SQL/Hive/Python
  • statistics
  • experimentation
  • causal inference techniques

Nice to have

  • Domain knowledge in ecosystem, ads, or real-time-bidding

What the JD emphasized

  • end to end ownership
  • web-scale data
  • scientific methods to solve real-world problems on web-scale data